{"id":"W175239712","doi":"10.1007/978-3-540-33187-2_13","title":"Connecting Arctic and Temperate Wetlands and Agricultural Landscapes: The Dynamics of Goose Populations in Response to Global Change","year":2006,"lang":"en","type":"book-chapter","venue":"Ecological studies","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Goose; Temperate climate; Wetland; Geography; Arctic; Ecology; Agriculture; Tundra; The arctic; Environmental change; Biology; Climate change; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003054606,0.0001464679,0.0002540543,0.00001675905,0.0002159032,0.00001091439,0.00006657347,0.0001439521,0.00006722593],"category_scores_gemma":[0.0002301192,0.00008493815,0.00002511398,0.00005715253,0.0001509094,0.00004628611,0.0002748737,0.0001256755,0.00001016724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001960042,"about_ca_system_score_gemma":0.000002584061,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001507775,"about_ca_topic_score_gemma":0.03704603,"domain_scores_codex":[0.9992728,0.00006739239,0.0002146013,0.0002285237,0.00007880885,0.0001378485],"domain_scores_gemma":[0.9994505,0.0003412205,0.0001021719,0.00006429871,0.00001411762,0.00002771334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007466442,0.00001902006,0.9945259,0.000009082026,0.00002217388,0.000006053884,0.0002883293,0.00006384707,0.000002237877,0.004107593,0.000394711,0.0004863923],"study_design_scores_gemma":[0.0001628066,0.000164674,0.9948606,0.00003003366,0.00002543498,0.000009305425,0.0003320187,0.00007215345,6.486919e-8,0.003704811,0.0005266566,0.0001114619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877433,0.0002543136,0.000001270924,0.006369757,0.00007003957,0.0003410363,0.00002742392,0.00001196398,0.00518086],"genre_scores_gemma":[0.9960594,0.00010409,0.00006151791,0.0003696503,0.00003026709,0.00003873161,0.00001345899,0.000003383673,0.003319521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03689525,"threshold_uncertainty_score":0.9805254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04686001697381109,"score_gpt":0.2676868013404097,"score_spread":0.2208267843665986,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}